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TensorFlow 1.x Deep Learning Cookbook

You're reading from   TensorFlow 1.x Deep Learning Cookbook Over 90 unique recipes to solve artificial-intelligence driven problems with Python

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788293594
Length 536 pages
Edition 1st Edition
Languages
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Authors (2):
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Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
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Toc

Table of Contents (15) Chapters Close

Preface 1. TensorFlow - An Introduction 2. Regression FREE CHAPTER 3. Neural Networks - Perceptron 4. Convolutional Neural Networks 5. Advanced Convolutional Neural Networks 6. Recurrent Neural Networks 7. Unsupervised Learning 8. Autoencoders 9. Reinforcement Learning 10. Mobile Computation 11. Generative Models and CapsNet 12. Distributed TensorFlow and Cloud Deep Learning 13. Learning to Learn with AutoML (Meta-Learning) 14. TensorFlow Processing Units

House price estimation-simple linear regression

In this recipe, we will perform simple linear regression based on the number of rooms (RM) on the Boston house price dataset.

Getting ready

Our goal is to predict the house price given in the last column (MEDV). In this recipe, we load the dataset from the TensorFlow Contrib dataset directly. We optimize the coefficients for an individual training sample using the stochastic gradient descent optimizer.

How to do it...

We proceed with the recipe as follows:

  1. The first step is to import all the packages that we will need:
...
You have been reading a chapter from
TensorFlow 1.x Deep Learning Cookbook
Published in: Dec 2017
Publisher: Packt
ISBN-13: 9781788293594
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